Terms & Templates
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| CI's for Dependent Means T-test | show 🗑
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| show | " -true difference between the two population means . . . "
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| Effect Size for ANOVA | show 🗑
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| show | Represents the likelihood that you would have obtained a T statistic this big IF the null hypothesis of no difference between the population means was actually true.
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| P-values for Dependent Means T-test | show 🗑
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| show | 1) Restate Q as a research Q and a null hypothesis about the pops. 2) Determine characteristics of the null comp dist. 3) Determine cut-offs that are unlikely enough to be rejected. 4) Compute sample's score & map it onto null comp dist. 5) decision.
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| Pearson Correlation | show 🗑
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| show | exploring associations between 2 or more numeric equal interval variables. - more than one predictor variable
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| T-test (Independent Means) | show 🗑
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| show | - comparing just two or less means. - diff participants in each condition.
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| show | - larger sample size - larger effect size -one tailed hypothesis test
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| show | - when you want to study an interaction effect to see if one IV depends on the other.
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| show | - tells how real an effect is. - speaks to the reality of an effect, but not the strength.
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| Effect Size | show 🗑
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| show | 1) determine nature of variables/research design 2) find+ review resources 3) run appropriate stat test/ check p-value to see if its below alpha 4) reject or fail to reject null hypothesis
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| Repeated Measures ANOVA | show 🗑
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| T-test (Dependent Means) | show 🗑
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| One-Way ANOVA | show 🗑
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| show | The null comparison distribution for the ANOVA that reflects the distribution of F-ratios, IF the null hypothesis of no population mean difference was true.
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| F-ratios in the middle region | show 🗑
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| F-ratios in the outside region | show 🗑
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| show | t = (sample mean - population mean) / Estimated SD
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| t score for dependent means T-test formula | show 🗑
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| F-ratio for an ANOVA formula | show 🗑
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